Feature Engineering for Interpretable Machine Learning for Quality Assurance in Radiation Oncology.

Pillai, Malvika; Adapa, Karthik; Shumway, John W; Dooley, John; Das, Shiva K; Chera, Bhishamjit S; Mazur, Lukasz

Pillai, Malvika; Adapa, Karthik; Shumway, John W; Dooley, John; Das, Shiva K; Chera, Bhishamjit S; Mazur, Lukasz.

Afiliación

Pillai M; Carolina Health Informatics Program, University of North Carolina, Chapel Hill, North Carolina.
Adapa K; Carolina Health Informatics Program, University of North Carolina, Chapel Hill, North Carolina.
Shumway JW; Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina.
Dooley J; Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina.
Das SK; Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina.
Chera BS; Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina.
Mazur L; Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina.

Stud Health Technol Inform ; 290: 460-464, 2022 Jun 06.

Article en En | MEDLINE | ID: mdl-35673057

Asunto(s)

Oncología por Radiación; Ingeniería; Aprendizaje Automático

Palabras clave

Machine learning; quality assurance; radiation oncology

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Oncología por Radiación Tipo de estudio: Prognostic_studies Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2022 Tipo del documento: Article

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